Defining a region of optimization based on engine usage data

ABSTRACT

Methods and systems for engine control optimization are provided. One or more operating conditions of a vehicle engine are detected. A value for each of a plurality of engine control parameters is determined based on the detected one or more operating conditions of the vehicle engine. A range of the most commonly detected operating conditions of the vehicle engine is identified and a region of optimization is defined based on the range of the most commonly detected operating conditions of the vehicle engine. The engine control optimization routine is initiated when the one or more operating conditions of the vehicle engine are within the defined region of optimization.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims priority to U.S. Provisional Application No.61/470,113, filed Mar. 31, 2011, and titled “ENGINE CONTROL OPTIMIZATIONUSING EXTREMUM SEEKING,” the entirety of which is incorporated herein byreference.

STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT

This invention was made with government support under grant No.DE-FC26-07NT43274 awarded by the Department of Energy. The governmenthas certain rights in the invention.

BACKGROUND

Embodiments of the present invention relate to real-time engine controloptimization.

SUMMARY

In one embodiment, the invention provides a method for engine controloptimization. One or more operating conditions of a vehicle engine aredetected. A value for each of a plurality of engine control parametersis determined, including a first engine control parameter and a secondengine control parameter, based on the detected one or more operatingconditions of the vehicle engine. A range of the most commonly detectedoperating conditions of the vehicle engine is identified and a region ofoptimization is defined based on the range of the most commonly detectedoperating conditions of the vehicle engine. The engine controloptimization routine is initiated when the one or more operatingconditions of the vehicle engine are within the defined region ofoptimization. The engine control optimization routine determines a valueof an engine performance variable, determines an initial value for thefirst engine control parameter and an initial value for the secondengine control parameter based on the detected one or more operatingconditions of the vehicle engine, and adjusts the initial value for thefirst engine control parameter and the initial value for the secondengine control parameter to cause the engine performance variable toapproach a target engine performance variable based on the determinedvalue of the engine performance variable.

In some embodiments, the engine control optimization routine determinesan optimum set-point for the first engine control parameter and anoptimum set-point for the second engine control parameter based on thedetermined value of the engine performance variable. Additionally, insome embodiments, the act of determining the optimum set-point for thefirst engine control parameter and the optimum set-point for the secondengine control parameter includes detecting when the first enginecontrol parameter has converged toward its optimum set-point, when thesecond engine control parameter has converged toward its optimumset-point, and when the engine performance variable approaches thetarget engine performance variable.

In another embodiment, the invention provides an engine controllercomprising a processor and a memory. The memory stores instructionsthat, when executed by the processor, cause the engine controller todetect an engine speed and an engine load, to determine a value for eachof a plurality of engine control parameters including a first enginecontrol parameter and a second engine control parameter based on thedetected engine speed and the detected engine load, to identify a rangeof the most commonly detected engine speeds and a range of the mostcommonly detected engine loads, and to define a region of optimizationbased on the range of the most commonly detected engine speeds and therange of the most commonly detected engine loads. The engine controllerinitiates an engine control optimization routine when the detectedengine speed and the detected engine load are within the defined regionof optimization. The engine control optimization routine determines avalue of fuel efficiency of a vehicle engine, determines an initialvalue for the first engine control parameter and an initial value forthe second engine control parameter based on the detected engine speedand the detected engine load, and adjusts the initial value for thefirst engine control parameter and the initial value for the secondengine control parameter to cause the fuel efficiency of the vehicleengine to approach a maximum fuel efficiency value based on thedetermined value of the fuel efficiency of the vehicle engine.

Other aspects of the invention will become apparent by consideration ofthe detailed description and accompanying drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a schematic illustration of a real-time engine controloptimization system including an engine having a speed sensor andpressure sensors, and an electronic control unit (“ECU”) having aprocessor, a memory, an extremum-seeking controller and a loadcontroller.

FIG. 2 illustrates a method by which the ECU controls the operation ofthe engine to achieve improved engine performance.

FIG. 3 illustrates an example of a real-time engine control systemoperating in a normal operating mode.

FIG. 4 provides a graphical representation of the engine map look-uptable for variable valve timing (“VVT”).

FIG. 5 provides a graphical representation of the engine map look-uptable for spark timing.

FIG. 6 illustrates operation of the real-time engine controloptimization system during the extremum-seeking (“ES”) optimization modeof the ECU.

FIG. 7 a illustrates an example of a generic form of the operation of anES controller used to apply an excitation to a control parameter.

FIG. 7 b illustrates an implementation of the ES controller adaptedspecifically to determine a spark timing offset value.

FIG. 8 illustrates a performance variable converging withinapproximately 20 seconds.

FIG. 9 a shows a graphical representation of an engine performancevariable such as an estimated net mean effective pressure (“NMEP”) forvarious combinations of VVT positions and combustion phase of θ_(CA50).

FIG. 9 b shows a graphical representation of another engine performancevariable—a net specific fuel consumption (“NSFC”) for variouscombinations of VVT positions and combustion phase of θ_(CA50).

FIG. 10 shows a graphical representation of how the optimization processadjusts an initial combination of engine control parameters until anoptimal combination of engine control parameters is attained.

FIG. 11 illustrates a method of updating the engine map look-up tablesstored on the memory of the ECU after completion of the ES optimizationprocess.

FIG. 12 a illustrates one example of an engine map look-up table storedby the ECU including nine operating sub-regions.

FIG. 12 b illustrates one example of an operating sub-region beingdivided into multiple smaller operating sub-regions to increase thespecificity of the engine map look-up table.

DETAILED DESCRIPTION

Before any embodiments of the invention are explained in detail, it isto be understood that the invention is not limited in its application tothe details of construction and the arrangement of components set forthin the following description or illustrated in the following drawings.The invention is capable of other embodiments and of being practiced orof being carried out in various ways.

FIG. 1 illustrates a real-time engine control optimization system 100for a vehicle. The system 100 is implemented on the vehicle and includesan engine 105 equipped with multiple sensors including, for example, aspeed sensor 110 and pressure sensors 115. An electronic control unit(“ECU”) 120 is in communication with the various sensors and actuatorsof the engine 105. The ECU 120 receives data from the speed sensor 110and the pressure sensors 115 and processes that data to control theoperation of the engine 105. The ECU 120 includes at least one processor135 and at least one memory 140. The memory 140 stores instructions thatare executed by the processor 135 to provide the functionality of theECU 120. Among other operations, the ECU 120 implements anextremum-seeking (“ES”) controller 125 and a load controller 130.

In some embodiments, the engine 105 is a modern internal combustionengine that is capable of operating on various blends of gasoline andethanol, also known as a flex-fuel engine. In some embodiments, theengine 105 is designed with advanced technologies such asdirect-injection (“DI”), turbocharging (“TC”), and variable valve timing(“VVT”). As described above, the ECU 120 receives data captured by thespeed sensor 110, the pressure sensors 115, and other sensors of theengine 105. The ECU 120 processes the received data and, as a result,operates the engine 105 such that target engine performance is achievedas described in further detail below. In particular, the ECU 120provides extremum seeking control that continually monitors how theengine 105 performs under specific operating conditions (e.g., enginespeed, engine load, etc.) when specific engine control parameters (e.g.,spark timing, variable valve timing, etc.) are applied. The ECU 120 usesthis information to adjust one or more engine control parameters toimprove the performance of the engine 105. For example, the ECU 120concurrently adjusts the spark timing and the variable valve timing ofthe engine 105 to achieve a maximum fuel efficiency of the engine 105.

FIG. 2 illustrates a method by which the ECU 120 controls the operationof the engine 105 to achieve improved engine performance. According tothis method, the ECU 120 switches between a normal operating mode and anES optimization mode. When operating in the normal mode, the ECU 120receives engine data captured by the speed sensor 110, the pressuresensors 115, and other sensors of the engine 105 (step 205). The ECU 120processes the data from the sensors and determines a value for each of aplurality of operating conditions of the engine 105, such as enginespeed and engine load, based on the sensor data (step 210). The ECU 120then determines whether the operating conditions fall within a region ofoptimization (step 215). The region of optimization is defined as arange of operating conditions where the ECU 120 will switch over to theES optimization control. The range of operating conditions isillustrated in FIGS. 4 and 5 and described in further detail below. Ifthe operating conditions do not fall within the region of optimization,the ECU 120 continues to run in the normal operating mode. The ECU 120accesses one or more pre-defined engine map look-up tables anddetermines appropriate engine control parameters (e.g., spark timing andvalve timing) based on the determined operating conditions (step 220).The ECU 120 then controls the operation of the engine 105 by applyingthe determined values for the engine control parameters to the engine105 (step 225). These steps are repeated at regular intervals as long asthe ECU 120 is operating in the normal mode. The normal operating modeis described in more detail below in reference to FIG. 3. If, however,the ECU 120 determines that the operating conditions of the vehicle fallwithin the region of optimization (step 215), the ECU 120 transitionsfrom the normal operating mode to the ES optimization mode. During theES optimization mode, the ECU 120 determines an initial value for eachof the plurality of engine control parameters based on the pre-definedengine map look-up tables (step 230). The ECU 120 then adjusts theinitial values for the engine control parameters based on the results ofan extremum seeking optimization process (step 235) before using theadjusted values for the engine control parameters to control operationof the engine 105 (step 240). The details of how the ES optimizationprocess adjusts the initial values of the engine control parameters isdescribed in further detail below in reference to FIG. 6.

The ECU 120 monitors one or more engine performance variables (e.g.,fuel efficiency) to determine if and when the engine performancevariable has converged toward a target value (step 245). In some cases,as described in further detail below, the target value will be a maximumor minimum achievable value for the engine performance variable. Inother cases, where multiple engine performance variables are monitored,the target variable is not a maximum or minimum achievable value, butrather a value defined by an optimal solution of multiple engineperformance variables.

If the engine performance variable has not converged toward the targetvalue (step 245), the ECU 120 receives new engine data captured by thesensors (step 250) and determines operating condition values based onthe received data from the sensors (step 255). The ECU 120 then verifiesthat the operating conditions of the vehicle engine 105 still fallwithin the region of optimization (step 260). As long as the operatingconditions of the engine 105 remain in the region of optimization (step260), the ECU 120 continues to operate in the ES optimization mode(steps 230, 235, 240, 245, 250, 255, and 260) until the engineperformance variable converges toward the target value. However, if theoperating conditions of the engine 105 are no longer within the regionof optimization, the ECU 120 transitions from the ES optimization modeto the normal operating mode.

When the engine performance variable has converged toward the targetvalue (step 245), the ECU 120 terminates the ES optimization mode (step265) and adjusts values in the pre-defined engine map look-up tablesbased on adjusted values of the engine control parameters applied to theengine 105 as the engine performance variable converges toward thetarget value (step 270). The process of updating the engine map look-uptables is described in further detail below in reference to FIGS. 11, 12a, and 12 b.

If the ECU 120 exits the ES optimization mode before the optimizationprocess is completed (step 260), the ECU 120 stores data from theoptimization process so that it can continue from where it left off whenthe operating conditions of the engine 105 re-enter the region ofoptimization (step 215). Furthermore, as described in detail below, theES optimization mode determines optimal control parameters thatcorrespond to specific operating conditions of the vehicle. As such, insome embodiments, if the operating conditions of the engine 105 changebefore the ES optimization is completed, but remain within the region ofoptimization, the ECU 120 terminates the ES optimization process andrestarts the ES optimization process for the new engine operatingconditions. In some embodiments, the ECU 120 again stores all data forincomplete ES optimizations so that the optimization process can beresumed when the engine operating conditions return to their previousvalues.

FIG. 3 illustrates, in greater detail, one example of a real-time enginecontrol system 100 operating in a normal operating mode. The ECU 120stores and employs an engine map look-up table for spark timing 305, anengine map look-up table for desired combustion phase 310, and an enginemap look-up table for variable valve timing 315. The ECU 120 receivesvalues indicative of engine speed (N), engine load (M), and cylinderpressure (p) from the engine sensors. The ECU 120 uses the engine maplook-up table 315 to determine an appropriate variable valve timing(“VVT”) based on the engine speed (N) and the engine load (M). The VVTincludes timing for an intake valve opening (“IVO”) and timing for anexhaust valve closing (“EVC”). An example of the engine map look-uptable for VVT 315 is illustrated in FIG. 4.

The ECU 120 utilizes the engine map look-up table 305 to determine aninitial value for the spark timing (θ_(s) ^(m)) based on the enginespeed (N) and the engine load (M). An example of the engine map look-uptable for spark timing 305 is illustrated in FIG. 5. This initial valueis offset by a determined value (Δθ_(s)) based on desired combustionphasing before the spark timing (θ_(s)) is applied to control theoperation of the engine 105. To determine the offset value (Δθ_(s)), theECU 120 uses the cylinder pressure measurements (p) from the pressuresensors 115 to calculate (module 325) a crank angle at which 50% of thetotal heat release has occurred (θ_(CA50)). This value (θ_(CA50)) isthen summed with the output of the engine map-look up table for desiredcombustion phase 310 and provided to a proportional-integral controller320. The initial value for the spark timing (θ_(s) ^(m)) is adjustedbased on the output (Δθ_(s)) of the PI controller 320, and the resultingspark timing (θ_(s)) is applied to control the operation of the engine105.

FIG. 4 provides a graphical representation of the engine map look-uptable for VVT 315. The engine map look-up table for VVT 315 defines aplurality of operating sub-regions 400. Each operating sub-regioncorresponds to a range of values for the engine speed (N) and a range ofvalues for the engine load (M) (i.e., the small squares on the graph).The engine map look-up table for VVT 315 defines a VVT valuecorresponding to each operating sub-region. The ECU 120 determines thevalue for the VVT, as discussed in the paragraphs above in reference toFIG. 3, by identifying a VVT value that corresponds to the detectedengine speed (N) and the detected engine load (M) as defined by theengine map look-up table for VVT 315.

FIG. 4 also illustrates a region of optimization 405. The region ofoptimization 405 includes a range of engine speed (N) values and engineload (M) values. The region of optimization 405 includes multipleoperating sub-regions within the engine map look-up table for VVT 315.The ECU 120 defines the region of optimization 405 based on a range ofthe most commonly detected engine speeds and a range of the mostcommonly detected engine loads including the operating conditions of theengine 105 at idle 410 and at a cruising speed 415. When the detectedengine speed (N) and the detected engine load (M) are within the definedregion of optimization 405, the ECU 120 recognizes that the engine 105is operating in the region of optimization 405 and initiates the ESoptimization mode.

As described in further detail below, after completing severalexecutions of the ES optimization for a specific operating sub-region,the ECU 120 overwrites corresponding value in the engine map look-uptable for VVT 315 based on an average optimal adjusted value of the VVT.As the ES optimization process is completed multiple times across eachoperating sub-region within the region of optimization 405, the ECU 120will eventually adjust the engine map look-up table 315 so that theoriginally defined values (represented by dotted lines 400) are changedto vehicle specific, optimal values for the VVT (represented by thesolid lines 420). For example, as illustrated in FIG. 4, the VVT valuecorresponding to an engine 105 operating in idle conditions isultimately adjusted from 410 to 425. Similarly, the VVT valuecorresponding to an engine 105 operating under cruising conditions isadjusted from 415 to 430.

FIG. 5 provides a graphical representation of the engine map look-uptable for spark timing 305. The engine map look-up table for sparktiming 305 also defines a plurality of operating sub-regions 500. Eachoperating sub-region corresponds to a range of values for the enginespeed (N) and a range of values for the engine load (M) (i.e., the smallsquares on the graph). The engine map look-up table for spark timing 305defines a spark timing value corresponding to each operating sub-region.The ECU 120 determines the value for the spark timing (θ_(s) ^(m)), asdiscussed in the paragraphs above in reference to FIG. 3, by identifyinga spark timing value that corresponds to the detected engine speed (N)and the detected engine load (M) as defined by the engine map look-uptable for spark timing 305.

FIG. 5 also illustrates a region of optimization 505 based on a range ofthe most commonly detected engine speeds and a range of the mostcommonly detected engine loads of the vehicle operating at idle 510. Inaddition, FIG. 5 illustrates another region of optimization 515 based ona range of the most commonly detected engine speeds and a range of themost commonly detected engine loads of the vehicle operating at acruising speed 520. As shown, the region of optimization 505 for thevehicle operating at idle 510 includes a different range of engine speed(N) values and engine load (M) values than the region of optimization515 for the vehicle operating at cruising speed 520. Both regions ofoptimization 505, 515 include multiple operating sub-regions within theengine map look-up table for spark timing 305. When the detected enginespeed (N) and the detected engine load (M) are within the defined regionof optimization 505, the ECU 120 recognizes that the engine 105 isoperating at idle 510 and initiates the ES optimization for the firstset of operating sub-regions. If the detected engine speed (N) and thedetected engine load (M) are within the other region of optimization515, the ECU 120 then recognizes that the engine 105 is operating atcruising speed 520 and initiates the ES optimization for the second setof operating sub-regions.

Similarly to the engine map look-up table for VVT 315, as discussed inthe paragraphs above in reference to FIG. 4, the ECU 120 will alsoadjust the engine map look-up table for spark timing 305 after multipleruns of the ES optimization are completed for each operating sub-regionwithin the region of optimization 505 for idle conditions and the regionof optimization 515 for cruising conditions. As shown in FIG. 5, theoriginally defined values (represented by dotted lines 500) are changedto vehicle specific, optimal values for the spark timing (represented bythe solid lines). For example, the spark timing value corresponding toan engine 105 operating in idle conditions is eventually adjusted from510 to 525. Similarly, the spark timing value corresponding to an engine105 operating under cruising conditions is adjusted from 520 to 530.

FIG. 6 illustrates, in the embodiment shown, operation of the real-timeengine control optimization system 100 during the ES optimization modeof the ECU 120. The ECU 120 employs the engine map look-up table forspark timing 305, the engine map look-up table for variable valve timing315, the ES controller 125, the load controller 130, and the real-timecalculation module 325 to determine the engine control parameters (e.g.,spark timing (θ_(s)) and VVT) and to regulate the detected value of theengine load (M). Outputs of the engine 105 including the cylinderpressure measurements (p) from the pressure sensors 115, engine speeddata (N) from the speed sensor 110, engine load data (M), and fuelquantity data (m_(f)) are received and processed by the ECU 120.

Using the cylinder pressure measurements (p) and the fuel quantity(m_(f)), the ECU 120 conducts real-time calculation 325 of a netspecific fuel consumption (“NSFC”) as well as other combustion featuressuch as the crank angle at which 50% of the total heat release hasoccurred (θ_(CA50)). Using the engine speed data (N) and the engine loaddata (M) from the sensors, the ECU 120 determines the operatingconditions of the engine 105 including the engine speed (N) and theengine load (M). The ECU 120 also utilizes a memory module 140, notshown in FIG. 3 or in FIG. 6, to store data such as the calculatedvalues of the crank angle at which 50% of the total heat release hasoccurred (θ_(CA50)). The calculated values of θ_(CA50) stored in thememory module 140 during the ES optimization mode are used to update theengine map look-up table for desired combustion phase 310, shown in FIG.3, during the normal operating mode of the ECU 120.

The detected engine speed (N) and the detected engine load (M) are usedas inputs to the engine map look-up table for spark timing 305 and theengine map look-up table for variable valve timing 315. The ECU 120utilizes the engine map look-up table for spark timing 305 to determinean initial value for the spark timing (θs^(m)) based on the detectedengine speed (N) and the detected engine load (M). The ECU 120 also usesthe engine map look-up table for VVT 315 to determine an initial valuefor the VVT (VVT^(m)) based on the detected engine speed (N) and thedetected engine load (M). As described in detail below, the ECU 120 usesthe Extremum Seeking (ES) controller 125 to determine a spark timingoffset value (Δθ_(s)) and a VVT offset value (ΔVVT). The spark timingoffset value (Δθ_(s)) and the VVT offset value (ΔVVT) are applied to theinitial values for the spark timing and VVT, respectively, beforeapplying an adjusted spark timing value (θ_(s)(k)) and an adjusted VVTvalue (VVT(k)) to the engine 105.

As illustrated in FIG. 6, the ECU 120 uses a spark timing engine maplook-up table 305 and a variable valve timing engine map look-up table315 to adjust two engine control variables concurrently. In someembodiments, the ECU 120 determines the adjusted values for each enginecontrol variable at different periods/frequencies. The ECU 120 can alsodetermine and apply the adjusted engine control parametersalternatingly. For example, the ECU 120 will first determine an adjustedspark timing. After applying the adjusted spark timing to the engine105, the ECU 120 then determines an adjusted VVT. After applying theadjusted VVT to the engine 105, the ECU 120 again adjusts the sparktiming value.

As described above, the ECU 120 uses the ES controller 125 to adjusteach engine control parameter to a value that will cause the engineperformance variable to approach a target value (e.g., a maximum or aminimum). However, changing the value of one engine control parameter(e.g., spark timing) results in a change in the operating state of thevehicle engine 105. As a result, the other engine control parameter(e.g., VVT) will also need to be adjusted to optimize the performance ofthe vehicle. Therefore, in some embodiments, when the ES optimizationprocess is used to concurrently adjust multiple engine controlparameters to achieve a target engine performance variable, adjustingthe initial value for one engine control parameter necessitates acorresponding adjustment of the second engine control parameter in orderto cause the engine performance variable to approach the target value.

The ECU 120 determines the spark timing offset value (Δθ_(s)) and theVVT offset value (ΔVVT) by applying the ES controller 125 to a value ofan engine performance variable such as the NSFC(k). The ES controller125 artificially perturbs the determined value of the engine performancevariable as described further below in reference to FIGS. 7 a and 7 b.Because the ES controller 125 determines the spark timing offset value(Δθ_(s)) and the VVT offset value (ΔVVT) based on the value of theengine performance variable, artificially perturbing the value of theperformance variable causes a perturbation of the determined offsetvalues.

FIG. 7 a illustrates an example of a generic form of the operation of anES controller 125 used to apply an excitation to a control parameter, todetermine an optimum set-point for the control parameter, and toartificially perturb a performance variable. The ES controller 125receives the calculated performance variable and applies a high-pass(“HP”) filter 705. The first-order HP filter 705 is defined by(z−1)/(z+h) where h is the HP filter cut-off frequency. An artificialperturbation (ε) signal is then applied (710) to the filteredperformance variable. The perturbation, ε, is chosen asε(k)=α(−1)^(k)  (1)where k is the iteration number which corresponds to a perturbation withamplitude α, frequency π/T, and phase shift π/2. A low-pass (“LP”)filter 715 is then applied to the artificially perturbed performancevariable. The first-order LP filter 715 is defined by (1−l)/(z−1)where/is the LP filter cut-off frequency. An integrator 720 is thenapplied to the filtered performance variable. The integrator 720 isdefined by T/(z−1). The artificial perturbation signal, ε(k), is thenadded (725) to the integrated performance variable to determine theengine control parameter offset value. The perturbation signal applied(710) to the performance variable can include, for example, a sinusoidalexcitation or a square-wave excitation. In some embodiments, theamplitude α of the perturbation signal ε(k) decays during the course ofa single run of the optimization process and reduces toward zero as theengine control parameter and, therefore, performance variable convergetoward the optimum values.

FIG. 7 b illustrates an implementation of the ES controller 125 adaptedspecifically to determine a spark timing offset value (Δθ_(s)). Asimilar ES controller process is used by the ES controller 125 of FIG. 6to concurrently determine a VVT offset value (ΔVVT). The ES controller125 of FIG. 7 b receives a value for the engine performance variable(i.e., NSFC(k)) and determines an offset value that causes the NSFC(k)to approach a target value.

The ES controller 125 of FIG. 7 b, applies an excitation to the sparktiming, artificially perturbing the engine performance variable, anddetecting whether the spark timing has converged toward an optimumset-point until the spark timing converges toward the optimum set-pointand the engine performance variable approaches the target engineperformance variable. The output of the ES controller 125 after the ESoptimization mode has ended is shown with a dotted line 730 and is usedin the act of updating the pre-defined engine map look-up table forspark timing 305.

The objective of the ES controller 125 to maximize an engine performancevariable such as fuel efficiency by manipulating an engine controlvariable such as spark timing is obtained by minimizing the net specificfuel consumption (“NSFC”), shown in FIG. 9 b below and defined by

$\begin{matrix}{{NSFC} = \frac{m_{i}}{W_{n}}} & (2)\end{matrix}$where m_(i) is the known injected fuel amount for each engine cycle andW_(n) is the net indicated work per cycle computed from the measuredcylinder pressure (p) and known volume V. The objective of the EScontroller 125 is to find the optimum spark timing (θ*_(s)), given by

$\begin{matrix}{\theta_{s}^{*} = {\arg_{\theta_{s}}^{\min}\left\{ {n_{c}{m_{i}\left( {\sum\limits_{k = 1}^{n_{c}}\;{\int{p_{k}{\mathbb{d}\; V}}}} \right)}^{- 1}} \right\}}} & (3)\end{matrix}$where n_(c) is the number of cylinders, p_(k) denotes the pressure incylinder k, and the integral is taken over the engine cycle of 720°. Thenet work W_(n) is the difference between the gross work W_(g) and thepumping work W_(p) which is approximated byW _(n) =W _(g) −W _(p) =m _(i) q _(1hv) n−(p _(em) −p _(im))V _(d)  (4)where q_(1hv) is the lower heating value of the fuel, n is the indicatedgross efficiency, (p_(em), p_(im)) are the exhaust and intake manifoldpressures respectively, and V_(d) is the displacement.

The amplitude (α) of the perturbation signal ε(k), discussed in theparagraphs above in reference to FIGS. 7 a and 7 b, is chosen to 1.5crank angle degrees (cad) as a compromise between good signal to noiseratio for the NSFC and an acceptable level of torque variations. Thesample time, denoted by T, is 30 engine cycles, thus

$\begin{matrix}{T = {30*\frac{120}{N}\mspace{14mu}({seconds})}} & (5)\end{matrix}$where N is the engine speed in revolutions per minute (“RPM”). Thesample time is chosen so that the engine 105 and the load controller 130can be approximated as a static nonlinearity for the NSFC as a functionof spark timing (θ_(s)). The value of the sample time is based onsimulations, showing that the settling time is less than 30 cycles fortypical steps in the commanded load.

The top graph of FIG. 8 shows a graphical representation of a sparktiming (θ_(s)) value provided by the engine map look-up table 305, anartificially introduced disturbance (or perturbation) (A), and aperturbed value of spark timing (θ_(s)+Δ) that is actually applied tothe engine 105. The bottom graph of FIG. 8 shows the determined engineperformance variable (e.g., NSFC) over the same time period for a totalof five different runs of the ES optimization routine. The ES controller125, discussed in reference to FIG. 7 b above, is alternatinglyactivated and de-activated. In the graphs of FIG. 8, the ES controller125 is de-activated during time periods marked by the gray areas. Asdiscussed above, the ES optimization routine ends when the performancevariable converges toward a value. The ES controller 125 of FIG. 7 bdetects whether the engine control parameter (e.g., spark timing θ_(s))has converged toward its optimum set-point (θ*_(s)) by monitoring theengine performance variable output (e.g., NSFC). The ES controller 125detects that convergence has occurred once the engine performancevariable output remains within a certain tolerance or does not exceedpredetermined maximum and minimum values for a specific amount of time.In the graphs of FIG. 8, the performance variable converges withinapproximately 20 seconds with an initial disturbance (Δ) of −12 cad fromthe optimum spark timing. During each run of optimization, the sparktiming (θ_(s)) converges toward its optimum set-point and the engineperformance variable (NSFC) converges toward a target value.

FIG. 9 a shows a graphical representation of an engine performancevariable such as an estimated net mean effective pressure (“NMEP”) forvarious combinations of VVT (or EVC-IVO) positions and combustion phaseof θ_(CA50). This graph illustrates that a maximum value of NMEP can beachieved by applying an optimal combination of engine control variables.The ECU 120 uses an ES controller 125, such as illustrated in FIGS. 7 aand 7 b, to adjust the engine control parameters until a combination isidentified that provides the maximum NMEP value.

Similarly, FIG. 9 b shows a graphical representation of another engineperformance variable—NSFC for various combinations of VVT positions andcombustion phase of θ_(CA50). This graph illustrates that a minimumvalue of NSFC can be achieved by applying an optimal combination ofengine control variables. The ECU 120 uses an ES controller 125, such asillustrated in FIGS. 7 a and 7 b, to adjust the engine controlparameters until a combination is identified that provides a minimumNSFC value.

In the examples illustrated in FIGS. 9 a and 9 b, the target value forthe engine performance variable is a maximum or minimum achievablevalue. However, in some circumstances, the target value for the engineperformance variable will not necessarily be a maximum or minimum value.In some embodiments, the ECU 120 uses the ES controller 125 toconcurrently optimize multiple engine performance variables. In somesuch cases, it is not possible to achieve maximum or minimum values forall of the engine performance variables. For example, the ES controller125 may be used to increase fuel efficiency and decrease vehicleemissions. However, the control parameters used to achieve maximum fuelefficiency may not provide the minimum achievable vehicle emissions. Insuch embodiments, the ECU 120 defines a cost function that balances thevalues for all of the performance variables to be optimized to achievean optimal solution instead of attempting to maximize or minimize thevalues of all of the engine performance variables. The cost function isdefined and stored to the ECU 120 and can be adjusted depending onconsiderations such as the type of vehicle, the intended usage of thevehicle, or local regulation (e.g., vehicle emissions laws).

FIG. 10 shows a graphical representation of how the optimization processadjusts an initial combination of engine control parameters (i.e., sparktiming and VVT) until an optimal combination of engine controlparameters is attained. Each additional run of the optimization process,performed by the ES controller 125, brings the combination of enginecontrol parameters closer to the optimal combination of engine controlparameters. Once determined, the optimal combination of engine controlparameters, as illustrated in FIG. 10, is applied to the engine 105 toachieve an optimal engine performance.

As described above, the ECU 120 uses engine map look-up tables todetermine initial values for control parameters based on detectedoperating conditions. When operating in the ES optimization mode, theECU 120 uses the functionality of the ES controller 125 to adjust thevalues of the control parameters from the engine map look-up tables toachieve a target value of an engine performance variable (e.g.,maximized fuel efficiency). The ECU 120 then uses the optimized valuesof the engine control parameters to update the engine map look-uptables. In this way, the control parameters provided by the look-uptables during subsequent engine operation will be closer to the optimalvalues. Furthermore, the ECU 120 can improve the specificity of theengine map look-up tables to provide more accurate optimization in areaswhere small changes to one or more control parameters cause relativelylarge changes in the engine performance variable.

FIG. 11 illustrates a method of updating the engine map look-up tablesstored on the memory 140 of the ECU 120 after completion of the ESoptimization process (step 1105). As described above, the ECU 120performs a separate ES optimization process for each operatingsub-region. FIG. 12 a illustrates one example of an engine map look-uptable stored by the ECU 120 including nine operating sub-regions.Operating sub-region “I” corresponds to engine loads between 70 and 80%and engine speeds from 2000-2100 RPM. Operating sub-region “II”corresponds to engine loads between 70 and 80% and engine speeds from2100-2200 RPM. Operating sub-regions “III”-“IX” are similarly defined byranges of engine speed and engine load. A value of an engine controlparameter (e.g., VVT or spark timing) is stored by the engine maplook-up table for each operating sub-region.

As described above, the end result after completion of an ESoptimization process for a particular operating sub-region (step 1105)is an optimized, converged value for one or more control parameterscorresponding to the particular operating sub-region. The ECU 120 storesthese converged values to the memory 140 after completion of each ESoptimization process. The ECU 120 then accesses a defined number ofconverged values stored on the memory 140 for the sub-region andcalculates an average converged value (step 1110). For example, if theES controller 125 is being used to determine an optimal VVT setting forthe operating sub-region, in one embodiment, the ECU 120 access theprevious five converged VVT values stored on the memory 140corresponding to previous optimization processes completed for theparticular operating sub-region and calculates the average.

Before overwriting the stored control parameter for the operatingsub-region in the engine map look-up table, the ECU 120 evaluates thesensitivity of the performance variable in the operating sub-region(step 1115). In this example, the ECU 120 determines a magnitude of achange in the fuel efficiency (the performance variable) of the engine105 resulting from a change in the VVT value. If the magnitude isgreater than a defined threshold, the ECU 120 adjusts the specificity ofthe engine map look-up table at the operating sub-region, as discussedin detail below. In other embodiments, the ECU 120 uses differentmethodology to evaluate the sensitivity of the engine performancevariable at a given operating sub-region. For example, the sensitivitymay be calculated based on how quickly the engine performance variable(e.g., fuel efficiency) responds to a change in a control parameter(VVT) or the sensitivity may be evaluated based on a combination ofspeed of change and magnitude of change.

If the sensitivity of the performance variable is less than thethreshold, the ECU 120 stores the average convergence value to theengine map look-up table overwriting the value corresponding to theoperating sub-region (step 1120). In some embodiment, the ECU 120applies a smoothing filter to the data in the engine map look-up tableto adjust control parameter values stored in the engine map look-uptable for operating sub-regions adjacent to the newly optimizedoperating sub-region. For example, if the ECU 120 changes the controlparameter value stored in the engine map look-up table for operatingsub-region “V,” the smoothing filter may adjust the control parametervalues stored in the engine map look-up table for operating sub-regionsI, II, III, IV, VI, VII, VIII, and IX based on the new value stored foroperating sub-region V.

As noted above, if the sensitivity of the engine performance variable atthe given operating sub-region is greater than a threshold, the ECU 120increases the specificity of the engine map look-up table for thatoperating sub-region by dividing the operating sub-region into multiple,smaller operating sub-regions (step 1125). FIG. 12 b illustrates oneexample of an operating sub-region being divided into multiple smalleroperating sub-regions to increase the specificity of the engine maplook-up table. In FIG. 12 b, operating sub-region “I” has been dividedinto four smaller operating sub-regions—IA, IB, IC, and ID. The ECU 120begins by storing the average convergence value for the previousoperating sub-region “I” to each of the new, smaller sub-regions IA, IB,IC, and ID (step 1130). The values stored for each of the new operatingsub-regions will be further adjusted when the ES optimization process issubsequently performed for each of the new operating sub-regions.

Thus, the invention provides, among other things, a system and methodfor optimizing the performance of a vehicle engine by perturbing theengine control parameters applied to the vehicle engine. Variousfeatures and advantages of the invention are set forth in the followingclaims.

What is claimed is:
 1. A method of engine control optimization, themethod comprising: detecting one or more operating conditions of avehicle engine; determining a value for each of a plurality of enginecontrol parameters including a first engine control parameter and asecond engine control parameter based on the detected one or moreoperating conditions of the vehicle engine; tracking a duration duringwhich a value of the one or more operating conditions are detectedduring operation of the vehicle engine; identifying a range of operatingcondition values including the values of the one or more operatingconditions that are detected for durations greater than a thresholdduration; defining a region of optimization based on the identifiedrange; and initiating an engine control optimization routine when theone or more operating conditions of the vehicle engine are within thedefined region of optimization, and wherein the engine controloptimization routine includes determining a value of an engineperformance variable, determining an initial value for the first enginecontrol parameter and an initial value for the second engine controlparameter based on the detected one or more operating conditions of thevehicle engine, and adjusting the initial value for the first enginecontrol parameter and the initial value for the second engine controlparameter to cause the engine performance variable to approach a targetengine performance variable based on the determined value of the engineperformance variable.
 2. The method of claim 1, wherein the enginecontrol optimization routine further includes repeating the acts ofdetermining the value of the engine performance variable, determiningthe initial value for the first engine control parameter and the initialvalue for the second engine control parameter based on the detected oneor more operating conditions of the vehicle engine, and adjusting theinitial value for the first engine control parameter and the initialvalue for the second engine control parameter based on the determinedvalue of the engine performance variable until the target engineperformance variable is achieved.
 3. The method of claim 1, wherein theact of detecting the one or more operating conditions of the vehicleengine includes detecting an engine speed and detecting an engine load.4. The method of claim 1, wherein the region of optimization includes arange of engine speeds and a range of engine loads.
 5. The method ofclaim 1, wherein the range of the most commonly detected operatingconditions includes the operating conditions of the vehicle engine at acruising speed.
 6. The method of claim 1, wherein at least one of thefirst engine control parameter and the second engine control parameterincludes a variable valve timing.
 7. The method of claim 6, wherein thevariable valve timing includes timing for an intake valve opening andtiming for an exhaust valve closing.
 8. The method of claim 1, whereinat least one of the first engine control parameter and the second enginecontrol parameter includes a spark timing.
 9. The method of claim 1,wherein the engine performance variable is a fuel efficiency of thevehicle engine.
 10. The method of claim 9, wherein the target engineperformance variable is a maximum value of the fuel efficiency of thevehicle engine.
 11. The method of claim 1, wherein determining the firstengine control parameter based on the detected one or more operatingconditions of the vehicle engine includes determining a value for thefirst engine control parameter that corresponds to the one or moreoperating conditions as defined by a first engine map look-up table. 12.The method of claim 11, wherein determining the second engine controlparameter based on the detected one or more operating conditions of thevehicle engine includes determining a value for the second enginecontrol parameter that corresponds to the one or more operatingconditions as defined by a second engine map look-up table.
 13. Themethod of claim 1, wherein the engine control optimization routinefurther includes determining an optimum set-point for the first enginecontrol parameter and an optimum set-point for the second engine controlparameter based on the determined value of the engine performancevariable.
 14. The method of claim 13, wherein the act of determining anoptimum set-point for the first engine control parameter and an optimumset-point for the second engine control parameter includes detectingwhen the first engine control parameter has converged toward its optimumset-point, when the second engine control parameter has converged towardits optimum set-point, and when the engine performance variableapproaches the target engine performance variable.
 15. An enginecontroller comprising a processor and a memory storing instructionsthat, when executed by the processor, cause the engine controller to:detect an engine speed and an engine load; determine a value for each ofa plurality of engine control parameters including a first enginecontrol parameter and a second engine control parameter based on thedetected engine speed and the detected engine load; track a durationduring which each combination of engine speed and engine load aredetected during operation of the vehicle engine; identify a range ofoperating conditions including combinations of engine speed and engineload that are detected for durations greater than a threshold duration;define a region of optimization based on the identified range; andinitiate an engine control optimization routine when the detected enginespeed and the detected engine load are within the defined region ofoptimization, and wherein the engine control optimization routineincludes determining a value of fuel efficiency of a vehicle engine,determining an initial value for the first engine control parameter andan initial value for the second engine control parameter based on thedetected engine speed and the detected engine load, and adjusting theinitial value for the first engine control parameter and the initialvalue for the second engine control parameter to cause the fuelefficiency of the vehicle engine to approach a maximum fuel efficiencyvalue based on the determined value of the fuel efficiency of thevehicle engine.